In Part 1 of this article, I explored the Seed-Group Loss Table as a predictive tool. The point of the exercise was to find patterns between seed-group losses and tournament performance. Since I added more information to the article, I would highly recommend reading (or re-reading it if you read it the first time) because I discussed a few more concepts about the data. In this article, we're going to be looking at the same data points, but the focus will be upon methods instead of data. Let's explore!
Feb 18, 2019
Feb 4, 2019
2019 Quality Curve Analysis - February Edition
Yes, it is the start of a new month, and at PPB, it usually means a new update to the Quality Curve Analysis. If you want to read the January Edition, here is the link. Before I jump into the article, a few quick thoughts are in order. First, the QC made a huge shift, one I didn't see coming and one for which I most likely don't have a full explanation. Second, I said in the previous edition for a high-magnitude shift to occur, shooting would have drastically improve. Well, shooting did slightly improve, but not enough to explain the magnitude in shift, so other unexplained factors exist. Third, the shift did not affect every team across the board, and for those that experienced the shift, it doesn't appear to be at the expense of others in the QC. Fourth and final, I should definitely point out the advanced metrics data being used includes all games played on January 31 and before. With that said, let's dive right into the analysis.
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